{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Binarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import Binarizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>advice</th>\n",
       "      <th>cab</th>\n",
       "      <th>decker</th>\n",
       "      <th>etis</th>\n",
       "      <th>eurobond</th>\n",
       "      <th>halligan</th>\n",
       "      <th>keen</th>\n",
       "      <th>pvr</th>\n",
       "      <th>refundable</th>\n",
       "      <th>soda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   advice  cab  decker  etis  eurobond  halligan  keen  pvr  refundable  soda\n",
       "0     0.0  0.0     2.0   0.0       0.0       0.0   0.0  0.0         0.0   0.0\n",
       "1     0.0  0.0     2.0   0.0       0.0       0.0   0.0  0.0         0.0   0.0\n",
       "2     1.0  0.0     0.0   0.0       0.0       0.0   0.0  0.0         0.0   0.0\n",
       "3     0.0  0.0     0.0   0.0       0.0       0.0   0.0  0.0         1.0   0.0\n",
       "4     0.0  0.0     2.0   0.0       0.0       0.0   0.0  0.0         0.0   0.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the bag of words dataset\n",
    "\n",
    "data = pd.read_csv(\"bag_of_words.csv\")\n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.dpi\"] = 450"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histograms to inspect variable distributions\n",
    "\n",
    "data.hist(bins=30, figsize=(20, 20), layout=(3, 4))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "advice         8\n",
       "cab            2\n",
       "decker         3\n",
       "etis           3\n",
       "eurobond       7\n",
       "halligan       5\n",
       "keen           4\n",
       "pvr            7\n",
       "refundable    35\n",
       "soda           3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>advice</th>\n",
       "      <th>cab</th>\n",
       "      <th>decker</th>\n",
       "      <th>etis</th>\n",
       "      <th>eurobond</th>\n",
       "      <th>halligan</th>\n",
       "      <th>keen</th>\n",
       "      <th>pvr</th>\n",
       "      <th>refundable</th>\n",
       "      <th>soda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.427954</td>\n",
       "      <td>0.008646</td>\n",
       "      <td>0.007925</td>\n",
       "      <td>0.007925</td>\n",
       "      <td>0.219020</td>\n",
       "      <td>0.072767</td>\n",
       "      <td>0.009366</td>\n",
       "      <td>0.177954</td>\n",
       "      <td>2.336455</td>\n",
       "      <td>0.007925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.940093</td>\n",
       "      <td>0.227675</td>\n",
       "      <td>0.110426</td>\n",
       "      <td>0.103691</td>\n",
       "      <td>0.695758</td>\n",
       "      <td>0.394309</td>\n",
       "      <td>0.144294</td>\n",
       "      <td>0.581526</td>\n",
       "      <td>6.151411</td>\n",
       "      <td>0.096488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            advice          cab       decker         etis     eurobond  \\\n",
       "count  1388.000000  1388.000000  1388.000000  1388.000000  1388.000000   \n",
       "mean      0.427954     0.008646     0.007925     0.007925     0.219020   \n",
       "std       0.940093     0.227675     0.110426     0.103691     0.695758   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "50%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "75%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "max       7.000000     6.000000     2.000000     2.000000    11.000000   \n",
       "\n",
       "          halligan         keen          pvr   refundable         soda  \n",
       "count  1388.000000  1388.000000  1388.000000  1388.000000  1388.000000  \n",
       "mean      0.072767     0.009366     0.177954     2.336455     0.007925  \n",
       "std       0.394309     0.144294     0.581526     6.151411     0.096488  \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
       "25%       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
       "50%       0.000000     0.000000     0.000000     1.000000     0.000000  \n",
       "75%       0.000000     0.000000     0.000000     2.000000     0.000000  \n",
       "max       4.000000     3.000000     6.000000    52.000000     2.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Binarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set up a Binarizer:\n",
    "\n",
    "binarizer = Binarizer(threshold=0).set_output(transform=\"pandas\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fit to data\n",
    "\n",
    "data_t = binarizer.fit_transform(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>advice</th>\n",
       "      <th>cab</th>\n",
       "      <th>decker</th>\n",
       "      <th>etis</th>\n",
       "      <th>eurobond</th>\n",
       "      <th>halligan</th>\n",
       "      <th>keen</th>\n",
       "      <th>pvr</th>\n",
       "      <th>refundable</th>\n",
       "      <th>soda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "      <td>1388.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.249280</td>\n",
       "      <td>0.001441</td>\n",
       "      <td>0.005764</td>\n",
       "      <td>0.006484</td>\n",
       "      <td>0.131844</td>\n",
       "      <td>0.041787</td>\n",
       "      <td>0.005043</td>\n",
       "      <td>0.112392</td>\n",
       "      <td>0.505764</td>\n",
       "      <td>0.007205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.432752</td>\n",
       "      <td>0.037946</td>\n",
       "      <td>0.075727</td>\n",
       "      <td>0.080292</td>\n",
       "      <td>0.338443</td>\n",
       "      <td>0.200174</td>\n",
       "      <td>0.070862</td>\n",
       "      <td>0.315962</td>\n",
       "      <td>0.500147</td>\n",
       "      <td>0.084604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            advice          cab       decker         etis     eurobond  \\\n",
       "count  1388.000000  1388.000000  1388.000000  1388.000000  1388.000000   \n",
       "mean      0.249280     0.001441     0.005764     0.006484     0.131844   \n",
       "std       0.432752     0.037946     0.075727     0.080292     0.338443   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "50%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "75%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "max       1.000000     1.000000     1.000000     1.000000     1.000000   \n",
       "\n",
       "          halligan         keen          pvr   refundable         soda  \n",
       "count  1388.000000  1388.000000  1388.000000  1388.000000  1388.000000  \n",
       "mean      0.041787     0.005043     0.112392     0.505764     0.007205  \n",
       "std       0.200174     0.070862     0.315962     0.500147     0.084604  \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
       "25%       0.000000     0.000000     0.000000     0.000000     0.000000  \n",
       "50%       0.000000     0.000000     0.000000     1.000000     0.000000  \n",
       "75%       0.000000     0.000000     0.000000     1.000000     0.000000  \n",
       "max       1.000000     1.000000     1.000000     1.000000     1.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_t.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oj92ttTtba19Kcm2fC7AiahRwKJvWOgDAcrXW3lNVJ80be+fYy1uT/Hh//pWdnCSfqKoDOzlJ38lJkqo6sJNzx2pmB454P5Pkuv58c0b16oA9fSxJ7p43fubBNlhV25NsT5KZmZnMzc0dNsTM0cnFp+0/7LylWMz7LsW+ffsmvs3VMIScQ8iYDCPnEDKu0ERrlPq0toaQcwgZk2HknERGjSJgI5v4FzGAlaqqX0myP8nVk9xua21Hkh1JsnXr1jY7O3vYdS6/+sZcdvtkdwfvOu/w77sUc3NzWcxnWWtDyDmEjMkwcg4h43KtRo1Sn9bWEHIOIWMyjJyTyKhRBGxIq/VFzF/E1tYQcg4hYzKMnEPIuFRVdUGSZyc5q7XW+vDeJCeOTdvSx3KIcYCJU6OARKMI2IBWcyfHX8TW1hByDiFjMoycQ8i4FFV1dpKXJfnh1tpDY4t2Jfn9qvqNJE9IckqS9yapJKdU1ckZ1aVzk/zUdFMDRwo1CjhAowjYUOzkAOtBVV2TZDbJ8VW1J8mlGV1c/5FJbq6qJLm1tfai1tpHqur6jK6Ntj/JRa21L/ftvDjJO5IcleTK1tpHpv5hgA1HjQIORaMIGCw7OcB61Vp7/gLDVxxi/muSvGaB8ZuS3DTBaABqFHBIGkXAYNnJAQAAmKyvW+sAAAAAAKwPGkUAAAAAJNEoAgAAAKDTKAIAAAAgiUYRAAAAAJ1GEQAAAABJNIoAAAAA6DSKAAAAAEiiUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQAAANBpFAEAAACQRKMIAAAAgE6jCAAAAIAkGkUAAAAAdBpFAAAAACTRKAIAAACgW1GjqKp+qao+UlUfrqprqupRVXVyVd1WVbur6rqqekSf+8j+endfftJEPgEAAAAAE7HsRlFVbU7y80m2ttaekuSoJOcmeV2S17fWnpTk/iQX9lUuTHJ/H399nwcAAADAOrHSU882JTm6qjYleXSSe5L8SJIb+vKdSZ7bn2/rr9OXn1VVtcL3BwAAAGBClt0oaq3tTfLrST6VUYPowSTvT/JAa21/n7Ynyeb+fHOSu/u6+/v845b7/gAAAABM1qblrlhVx2Z0lNDJSR5I8tYkZ680UFVtT7I9SWZmZjI3N7eo9WaOTi4+bf/hJy7BYt97sfbt2zfxba6GIeSUcXKGkhMAAIDVt+xGUZKnJflEa+2zSVJVb0vyg0mOqapN/aihLUn29vl7k5yYZE8/Ve1xST4/f6OttR1JdiTJ1q1b2+zs7KLCXH71jbns9pV8nIe767zFvfdizc3NZbGfZy0NIaeMkzOUnAAAAKy+lVyj6FNJnlpVj+7XGjoryR1J3p3kx/uc85Pc2J/v6q/Tl7+rtdZW8P4AAAAATNBKrlF0W0YXpf5Aktv7tnYkeXmSl1bV7oyuQXRFX+WKJMf18ZcmuWQFuQEAAACYsBWdq9VauzTJpfOG70xyxgJzv5DkJ1byfgAAAACsnpWcegYAAADABqJRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEArIqqurKq7q2qD4+NPb6qbq6qj/d/j+3jVVVvrKrdVfWhqjp9bJ3z+/yPV9X5a/FZgI1FfQIORaMIGDQ7OsA6dlWSs+eNXZLkltbaKUlu6a+T5JlJTumP7UnenIzqWUZ3mD0zo7vKXnqgpgGswFVRn4CD0CgChu6q2NEB1qHW2nuS3DdveFuSnf35ziTPHRt/Sxu5NckxVXVCkmckubm1dl9r7f4kN+fhNQ9gSdQn4FA2rXUAgJVorb2nqk6aN7wtyWx/vjPJXJKXZ2xHJ8mtVXVgR2c2fUcnSarqwI7ONaudHzjizLTW7unPP51kpj/fnOTusXl7+tjBxh+mqrZn1ATPzMxM5ubmDh/m6OTi0/YvIf7hLeZ9l2Lfvn0T3+ZqGELOIWRMhpFzCBmXQX1aoqH8Hgwh5xAyJsPIOYmMGkXARmRHZ4mG8H96yTByDiFjMoycQ8i4Eq21VlVtgtvbkWRHkmzdurXNzs4edp3Lr74xl90+2d3Bu847/PsuxdzcXBbzWdbaEHIOIWMyjJxDyLgS6tPiDOX3YAg5h5AxGUbOSWTUKAI2NDs6izOE/9NLhpFzCBmTYeQcQsZl+ExVndBau6cf0XhvH9+b5MSxeVv62N589QjJA+NzU8gJHHnUJyCJaxQBG9Nn+g5OlrCjs9A4wKTtSnLggvnnJ7lxbPwF/aL7T03yYD8y8h1Jnl5Vx/Zrpz29jwFMmvoEJNEoAjYmOzrAmquqa5L8eZInV9WeqrowyWuT/GhVfTzJ0/rrJLkpyZ1Jdif57SQ/lyT92mm/muR9/fGqA9dTA1gu9Qk4FKeeAYPWd3RmkxxfVXsyunvZa5Nc33d6PpnkeX36TUnOyWhH56EkL0xGOzpVdWBHJ7GjA0xAa+35B1l01gJzW5KLDrKdK5NcOcFowBFOfQIORaMIGDQ7OgAAAJPj1DMAAAAAkmgUAQAAANBpFAEAAACQRKMIAAAAgE6jCAAAAIAkGkUAAAAAdBpFAAAAACTRKAIAAACg0ygCAAAAIIlGEQAAAACdRhEAAAAASTSKAAAAAOg0igAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAICpqqpfqqqPVNWHq+qaqnpUVZ1cVbdV1e6quq6qHtHnPrK/3t2Xn7TG8YENTo0CNIqADclODrAeVdXmJD+fZGtr7SlJjkpybpLXJXl9a+1JSe5PcmFf5cIk9/fx1/d5AKtCjQKSFTaKquqYqrqhqv66qj5aVT9QVY+vqpur6uP932P73KqqN/YvYh+qqtMn8xEAvpadHGCd25Tk6KralOTRSe5J8iNJbujLdyZ5bn++rb9OX35WVdX0ogJHIDUKjnArPaLoDUn+pLX27Um+O8lHk1yS5JbW2ilJbumvk+SZSU7pj+1J3rzC9wY4FDs5wLrTWtub5NeTfCqjuvRgkvcneaC1tr9P25Nkc3++Ocndfd39ff5x08wMHDnUKCAZfZFalqp6XJIfSnJBkrTWvpTkS1W1Lclsn7YzyVySl2f0RewtrbWW5NZ+NNIJrbV7lp0eYAGttb1VdWAn5x+TvDNL2MmpqgM7OZ+banBgw+tHWm9LcnKSB5K8NcnZE9r29oz+GJeZmZnMzc0ddp2Zo5OLT9t/2HlLsZj3XYp9+/ZNfJurYQg5h5AxGUbOIWRcjtWqUerT2hpCziFkTIaRcxIZl90oyqh4fDbJ71bVd2f0JewXksyMNX8+nWSmP//KF7HuwJe0r2kULaeIJArJJA0hp4yTM5ScS+GL2NIN5fdgCDmHkDEZRs4hZFyGpyX5RGvts0lSVW9L8oNJjqmqTb2ZvSXJ3j5/b5ITk+zpR0g+LsnnF9pwa21Hkh1JsnXr1jY7O3vYMJdffWMuu30lu4MPd9d5h3/fpZibm8tiPstaG0LOIWRMhpFzCBmXaVVqlPq0toaQcwgZk2HknETGlfwvb1OS05O8pLV2W1W9IV89zSxJ0lprVdWWstHlFJFEIZmkIeSUcXKGknOJfBFboqH8Hgwh5xAyJsPIOYSMy/CpJE+tqkdndMTjWUn+Ism7k/x4kmuTnJ/kxj5/V3/95335u/rR2QCrQY0CVnSNoj1J9rTWbuuvb8iocfSZqjohSfq/9/blB76IHTD+JQ1gkr6yk9OvNXRWkjvy1Z2cZOGdnMRODrCK+n7TDUk+kOT2jPbFdmR0mv5Lq2p3Rqe+XtFXuSLJcX38pZn3RzmASVKjgGQFRxS11j5dVXdX1ZNbax/LV7+I3ZHRF67X5uFfxF5cVdcmOTPJg65PBKyGfpTjgZ2c/Un+MqOdnLcnubaqXt3Hxndyfq/v5NyX0R3SAFZFa+3SJJfOG74zyRkLzP1Ckp+YRi6ARI0CVnbqWZK8JMnVVfWIjIrHCzPqOl9fVRcm+WSS5/W5NyU5J8nuJA/1uQCrwk4OAADA0q2oUdRa+2CSrQssOmuBuS3JRSt5PwAAAABWz0quUQQAAADABqJRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAAA0GkUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0GkUAAAAAJNEoAgAAAKDTKAIAAAAgiUYRAAAAAJ1GEQAAAABJNIoAAAAA6DSKAACmqKqOqaobquqvq+qjVfUDVfX4qrq5qj7e/z22z62qemNV7a6qD1XV6WudH9jY1ChAowjYkOzkAOvYG5L8SWvt25N8d5KPJrkkyS2ttVOS3NJfJ8kzk5zSH9uTvHn6cYEjjBoFRziNImCjspMDrDtV9bgkP5TkiiRprX2ptfZAkm1JdvZpO5M8tz/fluQtbeTWJMdU1QlTDQ0cMdQoIEk2rXUAgEkb28m5IBnt5CT5UlVtSzLbp+1MMpfk5RnbyUlyaz8a6YTW2j1Tjg5sfCcn+WyS362q707y/iS/kGRmrOZ8OslMf745yd1j6+/pY+oTsBpWpUZV1faM/hiXmZmZzM3NHTbIzNHJxaftX/YHWchi3ncp9u3bN/FtroYh5BxCxmQYOSeRUaMI2IhW7YuYHZ21NYScQ8iYDCPnEDIuw6Ykpyd5SWvttqp6Q756dGOSpLXWqqotdcPq09oaQs4hZEyGkXMIGZdpVWpUa21Hkh1JsnXr1jY7O3vYdS6/+sZcdvtkv67edd7h33cp5ubmspjPstaGkHMIGZNh5JxERo0iYCNatS9idnTW1hByDiFjMoycQ8i4DHuS7Gmt3dZf35BRffrMgSMZ+2kb9/ble5OcOLb+lj72MOrT2hpCziFkTIaRcwgZl2nVahQwHK5RBGxEC+3knJ6+k5MkdnKAtdBa+3SSu6vqyX3orCR3JNmV5Pw+dn6SG/vzXUle0C+6/9QkDzotFlgtahSQOKII2IBaa5+uqrur6smttY/lqzs5d2S0c/PaPHwn58VVdW2SM2MnB1hdL0lydVU9IsmdSV6Y0R/vrq+qC5N8Msnz+tybkpyTZHeSh/pcgNWkRsERTqMI2Kjs5ADrUmvtg0m2LrDorAXmtiQXrXYmgAPUKECjCNiQ7OQAAAAsnWsUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0GkUAAAAAJJlAo6iqjqqqv6yqP+qvT66q26pqd1Vd129Nnap6ZH+9uy8/aaXvDQAAAMDkTOKIol9I8tGx169L8vrW2pOS3J/kwj5+YZL7+/jr+zwAAAAA1okVNYqqakuSZyX5nf66kvxIkhv6lJ1Jntufb+uv05ef1ecDAAAAsA5sWuH6v5nkZUke218fl+SB1tr+/npPks39+eYkdydJa21/VT3Y539ufINVtT3J9iSZmZnJ3NzcooLMHJ1cfNr+w09cgsW+92Lt27dv4ttcDUPIKePkDCUnAAAAq2/ZjaKqenaSe1tr76+q2UkFaq3tSLIjSbZu3dpmZxe36cuvvjGX3b7SvtfXuuu8xb33Ys3NzWWxn2ctDSGnjJMzlJwAAACsvpV0Vn4wyXOq6pwkj0ryjUnekOSYqtrUjyrakmRvn783yYlJ9lTVpiSPS/L5Fbw/AAAAABO07GsUtdZe0Vrb0lo7Kcm5Sd7VWjsvybuT/Hifdn6SG/vzXf11+vJ3tdbact8fAAAAgMmaxF3P5nt5kpdW1e6MrkF0RR+/IslxffylSS5ZhfcGAAAAYJkmclGf1tpckrn+/M4kZyww5wtJfmIS7wcAAADA5K3GEUUAAAAADJBGEQAAAABJNIoAAAAA6DSKAAAAAEiiUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQAAANBtWusAwOKddMnbJ77Nq85+zMS3CQAAwDA5oggAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIqADauqjqqqv6yqP+qvT66q26pqd1VdV1WP6OOP7K939+UnrWlwYMNTn4D1Sn0CNIqAjewXknx07PXrkry+tfakJPcnubCPX5jk/j7++j4PYDWpT8B6pT7BEU6jCNiQqmpLkmcl+Z3+upL8SJIb+pSdSZ7bn2/rr9OXn9XnA0yc+gSsV+oTkCSb1joAwCr5zSQvS/LY/vq4JA+01vb313uSbO7PNye5O0laa/ur6sE+/3NTSwscSX4zq1Cfqmp7ku1JMjMzk7m5ucMGmTk6ufi0/YedtxSLed+l2Ldv38S3uRqGkHMIGZNh5BxCxmX6zahPizaU34Mh5BxCxmQYOSeRUaMI2HCq6tlJ7m2tvb+qZie8bTs6a2gIOYeQMRlGziFkXKrVrE+ttR1JdiTJ1q1b2+zs4Td/+dU35rLbJ7s7eNd5h3/fpZibm8tiPstaG0LOIWRMhpFzCBmXSn1auqH8Hgwh5xAyJsPIOYmMGkXARvSDSZ5TVeckeVSSb0zyhiTHVNWm/lexLUn29vl7k5yYZE9VbUryuCSfX2jDdnTW1hByDiFjMoycQ8i4DKtWnwBWSH0CkrhGEbABtdZe0Vrb0lo7Kcm5Sd7VWjsvybuT/Hifdn6SG/vzXf11+vJ3tdbaFCMDRwj1CViv1CfgAI0i4Ejy8iQvrardGZ1Df0UfvyLJcX38pUkuWaN8wJFLfQLWK/UJjjBOPQM2tNbaXJK5/vzOJGcsMOcLSX5iqsGAI576BKxX6hMc2RxRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSrKBRVFUnVtW7q+qOqvpIVf1CH398Vd1cVR/v/x7bx6uq3lhVu6vqQ1V1+qQ+BAAAAAArt5IjivYnubi1dmqSpya5qKpOTXJJkltaa6ckuaW/TpJnJjmlP7YnefMK3hsAAACACVt2o6i1dk9r7QP9+d8n+WiSzUm2JdnZp+1M8tz+fFuSt7SRW5McU1UnLPf9AQAAAJisTZPYSFWdlOR7k9yWZKa1dk9f9OkkM/355iR3j622p4/dMzaWqtqe0RFHmZmZydzc3KIyzBydXHza/uV9gINY7Hsv1r59+ya+zdUwhJxHasZJ/44nw/hZAgAAMB0rbhRV1Tck+YMkv9ha+59V9ZVlrbVWVW0p22ut7UiyI0m2bt3aZmdnF7Xe5VffmMtun0jf6yvuOm9x771Yc3NzWeznWUtDyHmkZrzgkrdPdHtJctXZj1n3P0sAAACmY0V3Pauqr8+oSXR1a+1tffgzB04p6//e28f3JjlxbPUtfQwAAACAdWAldz2rJFck+Whr7TfGFu1Kcn5/fn6SG8fGX9DvfvbUJA+OnaIGAAAAwBpbyblaP5jk3yS5vao+2Md+Oclrk1xfVRcm+WSS5/VlNyU5J8nuJA8leeEK3hsAAACACVt2o6i19qdJ6iCLz1pgfkty0XLfDwAAAIDVtaJrFAEAAACwcWgUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAACSpqhOr6t1VdUdVfaSqfqGPP76qbq6qj/d/j+3jVVVvrKrdVfWhqjp9bT8BMAkaRcCGYycHWK/UJ2Cd25/k4tbaqUmemuSiqjo1ySVJbmmtnZLklv46SZ6Z5JT+2J7kzdOPDEyaRhGwEdnJAdYr9QlYt1pr97TWPtCf/32SjybZnGRbkp192s4kz+3PtyV5Sxu5NckxVXXCdFMDk6ZRBGw4dnKA9Up9Aoaiqk5K8r1Jbksy01q7py/6dJKZ/nxzkrvHVtvTx4AB27TWAQBW0wp3cu7JPFW1PaO/6mdmZiZzc3OHzTBzdHLxafuX9wEOYjHvuxT79u2b+DZXwxByDiFjMoycQ8i4EurT4gzl92AIOYeQMRlGziFkXImq+oYkf5DkF1tr/7OqvrKstdaqqi1xe+rTGhpCziFkTIaRcxIZNYqADWvSOzl9vR1JdiTJ1q1b2+zs7GHXufzqG3PZ7ZMtt3edd/j3XYq5ubks5rOstSHkHELGZBg5h5BxudSnxRvK78EQcg4hYzKMnEPIuFxV9fUZ1aerW2tv68OfqaoTWmv39KMa7+3je5OcOLb6lj72NdSntTWEnEPImAwj5yQyOvUM2JAOtZPTly95JwdgEtQnYL2qUdf6iiQfba39xtiiXUnO78/PT3Lj2PgL+oX3n5rkwbGjI4GB0igCNhw7OcB6pT4B69wPJvk3SX6kqj7YH+ckeW2SH62qjyd5Wn+dJDcluTPJ7iS/neTn1iAzMGFOPQM2ogM7ObdX1Qf72C9ntFNzfVVdmOSTSZ7Xl92U5JyMdnIeSvLCqaYFjiTqE7Butdb+NEkdZPFZC8xvSS5a1VDA1GkUARuOnRxgvVKfAID1zqlnAAAAACTRKAIAAACg0ygCAAAAIIlGEQAAAACdRhEAAAAASTSKAAAAAOg0igAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAAA0GkUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0U28UVdXZVfWxqtpdVZdM+/0BDkZ9AtYr9QlYr9Qn2Him2iiqqqOSvCnJM5OcmuT5VXXqNDMALER9AtYr9QlYr9Qn2Jg2Tfn9zkiyu7V2Z5JU1bVJtiW5Y8o5AOZTn4D1Sn2CFTjpkrdPfJtXnf2YiW9zoNQnWIH1Wp+m3SjanOTusdd7kpw55QwAC1GfYAXW647OBqE+AeuV+gQb0LQbRYdVVduTbO8v91XVxxa56vFJPjfRLK+b5NaSrELGVTKEnDJOyL963aJzPnG1swzBMmuU+jQ5Q8g5hIzJAHKqT0ujPq25IeQcQsZkADnVp6VRn9bcEHIOIWMygJyTqE/TbhTtTXLi2OstfewrWms7kuxY6oar6i9aa1tXFm91DSFjMoycMk7OUHJOwWHrU7K8GjWEn/EQMibDyDmEjMkwcg4h45SoT+s8YzKMnEPImAwj5xAyTon6tM4zJsPIOYSMyTByTiLjtO969r4kp1TVyVX1iCTnJtk15QwAC1GfgPVKfQLWK/UJNqCpHlHUWttfVS9O8o4kRyW5srX2kWlmAFiI+gSsV+oTsF6pT7AxTf0aRa21m5LctAqbXvLpamtgCBmTYeSUcXKGknPVqU+DMIScQ8iYDCPnEDJOhfo0CEPIOYSMyTByDiHjVKhPgzCEnEPImAwj54ozVmttEkEAAAAAGLhpX6MIAAAAgHVqcI2iqjq7qj5WVbur6pIFlj+yqq7ry2+rqpPWYcaXVtUdVfWhqrqlqqZ+28zDZRyb96+rqlXVmlzZfTE5q+p5/ef5kar6/fWWsaq+uareXVV/2f+bn7MGGa+sqnur6sMHWV5V9cb+GT5UVadPO+NGoD5NJ+PYPPVphRnVpyOH+jS9nGPz1qxGqU8Ty6g+TYH6NL2cY/PUpxVkPCLqU2ttMI+MLpD2t0m+JckjkvxVklPnzfm5JP+5Pz83yXXrMOO/SvLo/vzfrceMfd5jk7wnya1Jtq7T/96nJPnLJMf21/9iHWbckeTf9eenJrlrDX6WP5Tk9CQfPsjyc5L8cZJK8tQkt00749Af6tP0MvZ56tNkMqpPR8BDfZpuzj5vzWqU+jTRnOrT+vhdUJ8mlLPPU59WnnHD16ehHVF0RpLdrbU7W2tfSnJtkm3z5mxLsrM/vyHJWVVV6ylja+3drbWH+stbk2yZYr5FZex+NcnrknxhmuHGLCbnzyZ5U2vt/iRprd27DjO2JN/Ynz8uyd9NMd8oQGvvSXLfIaZsS/KWNnJrkmOq6oTppNsw1KcpZezUp8lkVJ+ODOrT5AyhRqlPE6I+TYX6NDnq0/Qybvj6NLRG0eYkd4+93tPHFpzTWtuf5MEkx00l3bz37xbKOO7CjDp903TYjP3QtBNba2+fZrB5FvOz/LYk31ZVf1ZVt1bV2VNLN7KYjK9M8tNVtSejO0K8ZDrRlmSpv7c8nPo0GerT5KhPHKA+Tc4QapT6ND3q08qpT5OjPk2G+pRk08TjsGhV9dNJtib54bXOMq6qvi7JbyS5YI2jLMamjA5PnM2oc/+eqjqttfbAWoaa5/lJrmqtXVZVP5Dk96rqKa21f17rYHAw6tNEqE+wCtZrfUoGVaPUJ1gF6tNEqE/rwNCOKNqb5MSx11v62IJzqmpTRoeCfX4q6ea9f7dQxlTV05L8SpLntNa+OKVsBxwu42OTPCXJXFXdldE5jbvW4GJni/lZ7kmyq7X2T621TyT5m4wKy7QsJuOFSa5Pktbanyd5VJLjp5Ju8Rb1e8shqU+ToT5NjvrEAerT5AyhRqlP06M+rZz6NDnq02SoT8ngLma9KcmdSU7OVy8s9Z3z5lyUr73Y2fXrMOP3ZnSBrFPW689x3vy5rM3FYhfzszw7yc7+/PiMDq87bp1l/OMkF/Tn35HROay1Bj/Pk3Lwi509K197sbP3Tjvf0B/q0/QyzpuvPq0so/p0BDzUp+nmnDd/6jVKfZp4VvVp7X8X1KcJ5Zw3X31afsYNX5+m+kEm9MM4J6Ou4t8m+ZU+9qqMOrfJqJv31iS7k7w3ybesw4z/LclnknywP3att4zz5k69iCzhZ1kZHUJ5R5Lbk5y7DjOemuTPepH5YJKnr0HGa5Lck+SfMurSX5jkRUleNPZzfFP/DLev1X/voT/Up+lknDdXfVpZRvXpCHmoT9PLOW/umtQo9WliGdWn9fG7oD5NKOe8uerT8jNu+PpUfSMAAAAAHOGGdo0iAAAAAFaJRhEAAAAASTSKAAAAAOg0igAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAAA0GkUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0GkUAAAAAJNEoAgAAAKDTKAIAAAAgiUYRAAAAAJ1GEQAAAABJNIoAAAAA6DSKAAAAAEiiUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQAAANBpFAEAAACQRKMIAAAAgE6jCAAAAIAkGkUAAAAAdBpFAAAAACTRKAIAAACg0ygCAAAAIIlGEQAAAACdRhEAAAAASTSKAAAAAOg0igAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOo4hVVVV3VdXTpvA+J1VVq6pNq/1ewPQtt5ZU1VxV/dv+/IKq+tOxZfuq6lsmmRNgIdPaHwKASfClGoAjUmvtG9Y6AwAArDeOKGLZHL0DAADAfL4rDptG0RGqqp5QVX9QVZ+tqk9U1c/38auq6tVj82aras/Y67uq6uVV9aEk/1BVm6rqOVX1kap6oJ/m8R3z3u77q+qOqrq/qn63qh41tr2frardVXVfVe2qqieMLWtV9aKq+njf9puqqvqyo6rq16vqc1V1Z5JnrdKPClg/vqeqPlRVD1bVdVX1qKo6tqr+qNey+/vzLYvZWK8xT+rPj6uqP6yq/1lV76uqV887Te0NVXV3X/7+qvpfxpa9sqqur6q3VNXf93q4dfIfH9gIquo7+r7X86vq2VX1wb6f8z+q6rvG5i24r9aXqTvAqunf+V4x/ztcVX20qp49Nm9Tr1Gnj10K5MKq+lSSd63hR2CFNIqOQFX1dUn+MMlfJdmc5Kwkv1hVz1jkJp6fUWPmmCTfkuSaJL+Y5JuS3JTkD6vqEWPzz0vyjCTfmuTbkvz7nuNHkvzHJM9LckKSTya5dt57PTvJ9yf5rj7vQMaf7cu+N8nWJD++yOzAcD0vydlJTs6oJlyQ0f+P/W6SJyb55iT/mOS3lrHtNyX5hyT/Msn5/THufUm+J8njk/x+kreON72TPCej+nVMkl3LzABscFV1epJ3JHlJkr9OcmWS/y3JcUn+S5JdVfXIRe6rqTvAalroO9w1GX0XPOAZST7XWvvA2NgPJ/mOfPV7GwOkUXRk+v4k39Rae1Vr7UuttTuT/HaScxe5/htba3e31v4xyU8meXtr7ebW2j8l+fUkRyf5/4zN/60+/74kr8lXi8t5Sa5srX2gtfbFJK9I8gNVddLYuq9trT3QWvtUkndn9EUtGX1h/M2x7f7Hpf0IgAF6Y2vt7/r/5v8wyfe01j7fWvuD1tpDrbW/z6jG/PBSNlpVRyX510ku7du5I8nO8Tmttf+7v9f+1tplSR6Z5MljU/60tXZTa+3LSX4vyXcv/2MCG9T/klFD5wWttT9Ksj3Jf2mt3dZa+3JrbWeSLyZ5aha3r6buAKtpoe9wv5/kOVX16D7npzJqHo17ZWvtH/p3RQbKeYNHpicmeUJVPTA2dlSS/zfJvYtY/+6x50/I6EigJElr7Z+r6u6M/vq10PxP9nUOrPuBsXX3VdXn+7p39eFPj637UJJvGFt3/naBjW1+PXhC31F5fUZHGh3blz22qo7qX54W45sy+v/D8Zoy/jxV9b8nuTCj2tOSfGOS4w+R7VFVtam1tn+RGYCN70VJ/ntrba6/fmKS86vqJWNzHpFRnflyDr6vdoC6A6ymh32Ha63trqqPJvmxqvrDjI5s/N5DrMdAOaLoyHR3kk+01o4Zezy2tXZORqdePHps7r9cYP029vzvMtrRSZL0awidmGTv2JwTx55/c19noXUfk9Gh1+PrHsw9C2wXOPJcnNGRPWe21r4xyQ/18VrCNj6bZH+S8WsbfaW+9OsRvSyjIxmPba0dk+TBJb4HwIuSfHNVvb6/vjvJa+btjz26tXZNDr2vBjANB/sOd+D0s21J7mit7Z63XguDp1F0ZHpvkr/vF6U+ul8Y+ilV9f1JPpjknKp6fFX9y4yuPXQo1yd5VlWdVVVfn9GXti8m+R9jcy6qqi1V9fgkv5Lkuj5+TZIXVtX3VNUjk/yHJLe11u5axGe4PsnP9+0em+SSxXxwYMN5bEbXJXqg15hLl7qBfuTR25K8sqoeXVXfnuQF895jf0YNpU1V9f/L6IgigKX4+4yOfvyhqnptRqeSvaiqzqyRx1TVs6rqsTn0vhrANBzsO9y1SZ6e5N9ldCoaG5BG0RGofyl6dkbX+/lEks8l+Z0kj8voHPe/yujUr3fmqwXhYNv6WJKfTnJ5386PJfmx1tqXxqb9ft/WnUn+Nsmr+7r/Lcn/meQPMjpC6Fuz+Osk/XZGF4P8q4xOX3vbItcDNpbfzOi6aJ9LcmuSP1nmdl6cUQ38dEZ18JqMmt7JqNb8SZK/yejQ6y/EYdXAMrTWHkjyo0memdFf4382o4tQ359kd0YX6T/cvhrANBzsO9w9Sf48o2vSHvK7IsNVrTkyDADGVdXrkvzL1tr8u58BAGxoVXVXkn/b/7DPEcgRRQAc8arq26vqu/rpH2dkdOHq/7rWuQAAYNrc9QwARtchuiajuw19JsllSW5c00QAALAGnHoGAAAAQBKnngEAAADQretTz44//vh20kknLWruP/zDP+Qxj3nM6gZaoSFkTIaRU8bJWWzO97///Z9rrX3TFCINxmJr1BB+F4aQMRlGziFkTIaRU31aPvVp+oaQcwgZk2HkVJ+WT32aviHkHELGZBg5J1KfWmvr9vF93/d9bbHe/e53L3ruWhlCxtaGkVPGyVlsziR/0dZBXVhPj8XWqCH8LgwhY2vDyDmEjK0NI6f6pD61NoyMrQ0j5xAytjaMnOqT+tTaMDK2NoycQ8jY2jByTqI+OfUMAAAAgCSuUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQCsiqq6sqruraoPL7Ds4qpqVXV8f11V9caq2l1VH6qq08fmnl9VH++P86f5GQCAI49GEQDA6rgqydnzB6vqxCRPT/KpseFnJjmlP7YneXOf+/gklyY5M8kZSS6tqmNXNTUAcETTKAIAWAWttfckuW+BRa9P8rIkbWxsW5K3tJFbkxxTVSckeUaSm1tr97XW7k9ycxZoPgEATIpGEQDAlFTVtiR7W2t/NW/R5iR3j73e08cONg4AsCo2rXUAAIAjQVU9OskvZ3Ta2Wpsf3tGp61lZmYmc3Nzh11n3759i5q3loaQMRlGziFkTIaRcwgZAZbrsI2iqroyybOT3Ntae0of+7UkP5bkS0n+NskLW2sP9GWvSHJhki8n+fnW2jv6+NlJ3pDkqCS/01p77cQ/DQDA+vWtSU5O8ldVlSRbknygqs5IsjfJiWNzt/SxvUlm543PLbTx1tqOJDuSZOvWrW12dnahaV9jbm4ui5m3loaQMRlGziFkTIaRcwgZAZZrMaeeXZWHnwt/c5KntNa+K8nfJHlFklTVqUnOTfKdfZ3/VFVHVdVRSd6U0YUaT03y/D4XAOCI0Fq7vbX2L1prJ7XWTsroNLLTW2ufTrIryQv63c+emuTB1to9Sd6R5OlVdWy/iPXT+xgAwKo4bKNooQsxttbe2Vrb31/emtFft5LRhRivba19sbX2iSS7M7pDxxlJdrfW7mytfSnJtX0uAMCGVFXXJPnzJE+uqj1VdeEhpt+U5M6M9p1+O8nPJUlr7b4kv5rkff3xqj4GALAqJnGNop9Jcl1/vjmjxtEB4xdcnH8hxjMn8N5fcfveB3PBJW+f5CZz12ufNdHtAUcm9QmOTK215x9m+Uljz1uSiw4y78okV040XKc+AeuV+gRrZ0WNoqr6lST7k1w9mTjLuxBjkswcnVx82v7DT1yCSV+gbigXvRtCThknZyg5AQAAWH3LbhRV1QUZXeT6rP5XsOTgF2LMIca/xnIuxJgkl199Yy67fbI3cbvrvMW992IN5aJ3Q8gp4+QMJScAAACrbzEXs36YfgezlyV5TmvtobFFu5KcW1WPrKqTk5yS5L0ZnVN/SlWdXFWPyOiC17tWFh0AAACASTpso+ggF2L8rSSPTXJzVX2wqv5zkrTWPpLk+iR3JPmTJBe11r7cL3z94ozu0vHRJNf3uQAAAExRVV1ZVfdW1YfHxn6tqv66qj5UVf+1qo4ZW/aKqtpdVR+rqmeMjZ/dx3ZX1SVT/hjAKjnsuVoHuRDjFYeY/5okr1lg/KaM7ugBAADA2rkqoz/+v2Vs7OYkr2it7a+q1yV5RZKXV9WpGZ0R8p1JnpDkv1XVt/V13pTkRzO6WdH7qmpXa+2OKX0GYJUs69QzAAAAhqm19p4k980be2c/EyQZ3cl6S3++Lcm1rbUvttY+kWR3kjP6Y3dr7c7W2peSXNvnAgM32as/AwAAMHQ/k+S6/nxzRo2jA/b0sSS5e974mQttbDl3tnZX68kZQs4hZEyGkXMSGTWKAAAASJJU1a8k2Z/k6kltczl3tnZX68kZQs4hZEyGkXMSGTWKAAAASFVdkOTZSc5qrbU+vDfJiWPTtvSxHGIcGDDXKAIAADjCVdXZSV6W5DmttYfGFu1Kcm5VPbKqTk5ySpL3JnlfklOq6uSqekRGF7zeNe3cwOQ5oggAAOAIUlXXJJlNcnxV7UlyaUZ3OXtkkpurKkluba29qLX2kaq6PskdGZ2SdlFr7ct9Oy9O8o4kRyW5srX2kal/GGDiNIoAAACOIK215y8wfMUh5r8myWsWGL8pyU0TjAasA049AwAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAAA0GkUAQAAAJBEowgYsKq6sqruraoPj439WlX9dVV9qKr+a1UdM7bsFVW1u6o+VlXPGBs/u4/trqpLpvwxAAAA1g2NImDIrkpy9ryxm5M8pbX2XUn+JskrkqSqTk1ybpLv7Ov8p6o6qqqOSvKmJM9McmqS5/e5AAAARxyNImCwWmvvSXLfvLF3ttb295e3JtnSn29Lcm1r7YuttU8k2Z3kjP7Y3Vq7s7X2pSTX9rkAAABHHI0iYCP7mSR/3J9vTnL32LI9fexg4wAAAEecTWsdAGA1VNWvJNmf5OoJb3d7ku1JMjMzk7m5ucOuM3N0cvFp+w87bykW875LsW/fvolvczUMIecQMibDyDmEjAAAG41GEbDhVNUFSZ6d5KzWWuvDe5OcODZtSx/LIcYfprW2I8mOJNm6dWubnZ09bJ7Lr74xl90+2XJ713mHf9+lmJuby2I+y1obQs4hZEyGkXMIGQEANhqnngEbSlWdneRlSZ7TWntobNGuJOdW1SOr6uQkpyR5b5L3JTmlqk6uqkdkdMHrXdPODQAAsB44oggYrKq6JslskuOrak+SSzO6y9kjk9xcVUlya2vtRa21j1TV9UnuyOiUtItaa1/u23lxknckOSrJla21j0z9wwAAAKwDGkXAYLXWnr/A8BWHmP+aJK9ZYPymJDdNMBoAAMAgOfUMAAAAgCQaRQAAE1dVV1bVvVX14bGxX6uqv66qD1XVf62qY8aWvaKqdlfVx6rqGWPjZ/ex3VV1yZQ/BgBwBNIoAgCYvKuSnD1v7OYkT2mtfVeSv8nommqpqlMzupD+d/Z1/lNVHVVVRyV5U5JnJjk1yfP7XACAVaNRBAAwYa219yS5b97YO1tr+/vLW5Ns6c+3Jbm2tfbF1tonkuxOckZ/7G6t3dla+1KSa/tcAIBV42LWAADT9zNJruvPN2fUODpgTx9LkrvnjZ95sA1W1fYk25NkZmYmc3Nzhw0xc3Ry8Wn7DztvKRbzvkuxb9++iW9zNQwh5xAyJsPIOYSMAMulUQQAMEVV9StJ9ie5epLbba3tSLIjSbZu3dpmZ2cPu87lV9+Yy26f7O7gXecd/n2XYm5uLov5LGttCDmHkDEZRs4hZARYLo0iAIApqaoLkjw7yVmttdaH9yY5cWzalj6WQ4wDAKwK1ygCAJiCqjo7ycuSPKe19tDYol1Jzq2qR1bVyUlOSfLeJO9LckpVnVxVj8jogte7pp0bADiyOKIIAGDCquqaJLNJjq+qPUkuzeguZ49McnNVJcmtrbUXtdY+UlXXJ7kjo1PSLmqtfblv58VJ3pHkqCRXttY+MvUPAwAcUTSKAAAmrLX2/AWGrzjE/Nckec0C4zcluWmC0QAADsmpZwAAAAAk0SgCAAAAoDtso6iqrqyqe6vqw2Njj6+qm6vq4/3fY/t4VdUbq2p3VX2oqk4fW+f8Pv/jVXX+6nwcAAAAAJZrMUcUXZXk7HljlyS5pbV2SpJb+uskeWZGd+o4Jcn2JG9ORo2ljC7ieGaSM5JceqC5BAAAAMD6cNhGUWvtPUnumze8LcnO/nxnkueOjb+ljdya5JiqOiHJM5Lc3Fq7r7V2f5Kb8/DmEwAAAABraLnXKJpprd3Tn386yUx/vjnJ3WPz9vSxg40DAAAAsE5sWukGWmutqtokwiRJVW3P6LS1zMzMZG5ublHrzRydXHza/knFSJJFv/di7du3b+LbXA1DyCnj5AwlJwAAAKtvuY2iz1TVCa21e/qpZff28b1JThybt6WP7U0yO298bqENt9Z2JNmRJFu3bm2zs7MLTXuYy6++MZfdvuK+19e467zFvfdizc3NZbGfZy0NIaeMkzOUnAAATEZVXZnk2Unuba09pY89Psl1SU5KcleS57XW7q+qSvKGJOckeSjJBa21D/R1zk/y7/tmX91a2xlg8JZ76tmuJAfuXHZ+khvHxl/Q73721CQP9lPU3pHk6VV1bL+I9dP7GAAAANN1VdywCDiIwzaKquqaJH+e5MlVtaeqLkzy2iQ/WlUfT/K0/jpJbkpyZ5LdSX47yc8lSWvtviS/muR9/fGqPgYAAMAUuWERcCiHPVertfb8gyw6a4G5LclFB9nOlUmuXFI6AAAApsENi4AkE7iYNQAAABvHerhhkZsVTc4Qcg4hYzKMnJPIqFEEAADAurphkZsVTc4Qcg4hYzKMnJPIuNyLWQMAALBxuGERkMQRRQAAAEeUfsOi2STHV9WejO5e9tok1/ebF30yyfP69JuSnJPRDYseSvLCZHTDoqo6cMOixA2LYMPQKAIAADiCuGERcChOPQMAAAAgiUYRAAAAAJ1GEQAAAABJNIoAAAAA6DSKAAAAAEiiUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQNXVVdW1b1V9eGxscdX1c1V9fH+77F9vKrqjVW1u6o+VFWnj61zfp//8ao6fy0+CwAAwFrTKAKG7qokZ88buyTJLa21U5Lc0l8nyTOTnNIf25O8ORk1lpJcmuTMJGckufRAcwkAAOBIolEEDFpr7T1J7ps3vC3Jzv58Z5Lnjo2/pY3cmuSYqjohyTOS3Nxau6+1dn+Sm/Pw5hMAAMCGt2mtAwCsgpnW2j39+aeTzPTnm5PcPTZvTx872PjDVNX2jI5GyszMTObm5g4f5ujk4tP2LyH+4S3mfZdi3759E9/mahhCziFkTIaRcwgZAQA2Go0iYENrrbWqahPc3o4kO5Jk69atbXZ29rDrXH71jbns9smW27vOO/z7LsXc3FwW81nW2hByDiFjMoycQ8gIALDROPUM2Ig+008pS//33j6+N8mJY/O29LGDjQMAABxRNIqAjWhXkgN3Ljs/yY1j4y/odz97apIH+ylq70jy9Ko6tl/E+ul9DAAA4Iji1DNg0KrqmiSzSY6vqj0Z3b3stUmur6oLk3wyyfP69JuSnJNkd5KHkrwwSVpr91XVryZ5X5/3qtba/AtkAwAAbHgaRcCgtdaef5BFZy0wtyW56CDbuTLJlROMBhzhqurKJM9Ocm9r7Sl97PFJrktyUpK7kjyvtXZ/VVWSN2TUzH4oyQWttQ/0dc5P8u/7Zl/dWtsZAIBV4tQzAIDVcVWSs+eNXZLkltbaKUlu6a+T5JlJTumP7UnenHylsXRpkjOTnJHk0n6KLADAqtAoAgBYBa219ySZfxrrtiQHjgjameS5Y+NvaSO3JjmmX4z/GUlubq3d11q7P8nNeXjzCQBgYpx6BgAwPTP9IvpJ8ukkM/355iR3j83b08cONv4wVbU9o6ORMjMzk7m5ucOHOTq5+LT9S4h/eIt536XYt2/fxLe5GoaQcwgZk2HkHEJGgOXSKAIAWAOttVZVbYLb25FkR5Js3bq1zc7OHnady6++MZfdPtndwbvOO/z7LsXc3FwW81nW2hByDiFjMoycQ8gIsFxOPQMAmJ7P9FPK0v+9t4/vTXLi2Lwtfexg4wAAq0KjCABgenYlOb8/Pz/JjWPjL6iRpyZ5sJ+i9o4kT6+qY/tFrJ/exwAAVoVTzwAAVkFVXZNkNsnxVbUno7uXvTbJ9VV1YZJPJnlen35TknOS7E7yUJIXJklr7b6q+tUk7+vzXtVam3+BbACAidEoAgBYBa215x9k0VkLzG1JLjrIdq5McuUEowEAHJRTzwAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBuRY2iqvqlqvpIVX24qq6pqkdV1clVdVtV7a6q66rqEX3uI/vr3X35SRP5BAAAAABMxLIbRVW1OcnPJ9naWntKkqOSnJvkdUle31p7UpL7k1zYV7kwyf19/PV9HgAAAADrxEpPPduU5Oiq2pTk0UnuSfIjSW7oy3cmeW5/vq2/Tl9+VlXVCt8fAAAAgAnZtNwVW2t7q+rXk3wqyT8meWeS9yd5oLW2v0/bk2Rzf745yd193f1V9WCS45J8bny7VbU9yfYkmZmZydzc3KLyzBydXHza/sNPXILFvvdi7du3b+LbXA1DyCnj5AwlJwAAAKtv2Y2iqjo2o6OETk7yQJK3Jjl7pYFaazuS7EiSrVu3ttnZ2UWtd/nVN+ay25f9cRZ013mLe+/Fmpuby2I/z1oaQk4ZJ2coOQEAWH1V9UtJ/m2SluT2JC9MckKSazP6Q//7k/yb1tqXquqRSd6S5PuSfD7JT7bW7lqL3MDkrOTUs6cl+URr7bOttX9K8rYkP5jkmH4qWpJsSbK3P9+b5MQk6csfl1ExAQAAYI25Di2QrKxR9KkkT62qR/drDZ2V5I4k707y433O+Ulu7M939dfpy9/VWmsreH8AAAAmy3Vo4Qi3kmsU3VZVNyT5QJL9Sf4yo1PG3p7k2qp6dR+7oq9yRZLfq6rdSe7LqDMNAADAOrCerkPrGrSTM4ScQ8iYDCPnJDKu6KI+rbVLk1w6b/jOJGcsMPcLSX5iJe8HAADA6lhP16F1DdrJGULOIWRMhpFzEhlXcuoZAAAAG4fr0AIaRQAAACRxHVogGkUAAABkdB3ajC5K/YEkt2f0fXFHkpcneWm/3uxx+drr0B7Xx1+a5JKphwYmbrInfQIAADBYrkMLOKIIAAAAgCQaRQAAAAB0GkUAAAAAJNEoAgAAAKDTKAIAAAAgiUYRsEFV1S9V1Ueq6sNVdU1VPaqqTq6q26pqd1VdV1WP6HMf2V/v7stPWuP4AAAAa0KjCNhwqmpzkp9PsrW19pQkRyU5N8nrkry+tfakJPcnubCvcmGS+/v46/s8AACAI45GEbBRbUpydFVtSvLoJPck+ZEkN/TlO5M8tz/f1l+nLz+rqmp6UQEAANaHTWsdAGDSWmt7q+rXk3wqyT8meWeS9yd5oLW2v0/bk2Rzf745yd193f1V9WCS45J8bv62q2p7ku1JMjMzk7m5ucPmmTk6ufi0/YedtxSLed+l2Ldv38S3uRqGkHMIGZNh5BxCRgCAjUajCNhwqurYjI4SOjnJA0nemuTsSWy7tbYjyY4k2bp1a5udnT3sOpdffWMuu32y5fau8w7/vksxNzeXxXyWtTaEnEPImAwj5xAyAgBsNE49AzaipyX5RGvts621f0rytiQ/mOSYfipakmxJsrc/35vkxCTpyx+X5PPTjQwAALD2NIqAjehTSZ5aVY/u1xo6K8kdSd6d5Mf7nPOT3Nif7+qv05e/q7XWppgXOIK4KyMAsJ5pFAEbTmvttowuSv2BJLdnVOt2JHl5kpdW1e6MrkF0RV/liiTH9fGXJrlk6qGBI4K7MgIA651rFAEbUmvt0iSXzhu+M8kZC8z9QpKfmEYugHz1roz/lK+9K+NP9eU7k7wyyZszut7aK/v4DUl+q6rKUY8AwGpxRBEAwJS01vYmOXBXxnuSPJgl3JWxzz9umpkBgCOLI4oAAKZkNe/KWFXbk2xPkpmZmczNzR12nZmjk4tP23/YeUuxmPddin379k18m6thCDmHkDEZRs4hZARYLo0iAIDp+cpdGZOkqr7mroz9qKGF7sq453B3ZWyt7cjoemzZunVrm52dPWyYy6++MZfdPtndwbvOO/z7LsXc3FwW81nW2hByDiFjMoycQ8gIsFxOPQMAmB53ZQQA1jWNIgCAKXFXRgBgvXPqGQDAFLkrIwCwnjmiCAAAAIAkGkUAAAAAdBpFAAAAACTRKAIAAACg0ygCAAAAIIlGEQAAAACdRhEAAAAASTSKAAAAAOg0igAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkGSFjaKqOqaqbqiqv66qj1bVD1TV46vq5qr6eP/32D63quqNVbW7qj5UVadP5iMAAAAAMAkrPaLoDUn+pLX27Um+O8lHk1yS5JbW2ilJbumvk+SZSU7pj+1J3rzC9wYAAABggpbdKKqqxyX5oSRXJElr7UuttQeSbEuys0/bmeS5/fm2JG9pI7cmOaaqTlju+wMAAAAwWZtWsO7JST6b5Her6ruTvD/JLySZaa3d0+d8OslMf745yd1j6+/pY/eMjaWqtmd0xFFmZmYyNze3qDAzRycXn7Z/WR/kYBb73ou1b9++iW9zNQwhp4yTM5ScAACsvqo6JsnvJHlKkpbkZ5J8LMl1SU5KcleS57XW7q+qyugsk3OSPJTkgtbaB6afGpiklTSKNiU5PclLWmu3VdUb8tXTzJIkrbVWVW0pG22t7UiyI0m2bt3aZmdnF7Xe5VffmMtuX8nHebi7zlvcey/W3NxcFvt51tIQcso4OUPJCQDAVBy4vMiPV9Ujkjw6yS9ndHmR11bVJRl973t5vvbyImdmdHmRM9cmNjApK7lG0Z4ke1prt/XXN2TUOPrMgVPK+r/39uV7k5w4tv6WPgYAAMAac3kRIFnBEUWttU9X1d1V9eTW2seSnJXkjv44P8lr+7839lV2JXlxVV2bUZf5wbFT1AAAAFhb6+byIi4tMjlDyDmEjMkwck4i40rP1XpJkqv7IYl3JnlhRkcpXV9VFyb5ZJLn9bk3ZXTu6u6Mzl994QrfGwAAgMlZN5cXcWmRyRlCziFkTIaRcxIZV/S/vNbaB5NsXWDRWQvMbUkuWsn7AQAAsGoWurzIJemXF2mt3ePyIrDxreQaRQAAAGwQrbVPJ7m7qp7chw5cXmRXRpcVSR5+eZEX1MhT4/IisCFM9lg+AAAAhszlReAIp1EEAABAEpcXAZx6BgAAAECnUQRsSFV1TFXdUFV/XVUfraofqKrHV9XNVfXx/u+xfW5V1RurandVfaiqTl/r/AAAAGtBowjYqN6Q5E9aa9+e5LuTfDSju3bc0lo7Jckt+ertXp+Z5JT+2J7kzdOPCwAAsPY0ioANp6oel+SHklyRJK21L7XWHkiyLcnOPm1nkuf259uSvKWN3JrkmH7rVwAAgCOKi1kDG9HJST6b5Her6ruTvD/JLySZGbtl66eTzPTnm5PcPbb+nj72sNu7VtX2jI46yszMTObm5g4bZubo5OLT9i/rgxzMYt53Kfbt2zfxba6GIeQcQsZkGDmHkBEAYKPRKAI2ok1JTk/yktbabVX1hnz1NLMko7t0VFVb6oZbazuS7EiSrVu3ttnZ2cOuc/nVN+ay2ydbbu867/DvuxRzc3NZzGdZa0PIOYSMyTByDiEjAMBG49QzYCPak2RPa+22/vqGjBpHnzlwSln/996+fG+SE8fW39LHACbOxfYBgPVMowjYcFprn05yd1U9uQ+dleSOJLuSnN/Hzk9yY3++K8kL+heypyZ5cOwUNYBJc7F9AGDdcuoZsFG9JMnVVfWIJHcmeWFGzfHrq+rCJJ9M8rw+96Yk5yTZneShPhdg4sYutn9BMrrYfpIvVdW2JLN92s4kc0lenrGL7Se5tR+NdIJmNgCwWjSKgA2ptfbBJFsXWHTWAnNbkotWOxNAXGx/yYZyUfMh5BxCxmQYOYeQEWC5NIoAAKbHxfaXaCgXNR9CziFkTIaRcwgZAZbLNYoAAKbHxfYBgHVNowgAYEpcbB8AWO+cegYAMF0utg8ArFsaRQAAU+Ri+wDAeubUMwAAAACSaBQBAAAA0GkUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0GkUAAAAAJNEoAgAAAKDTKAIAAAAgiUYRAAAAAJ1GEQAAAABJNIoAAAAA6DSKAAAAAEiiUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQAAANBpFAEAAACQRKMIAAAAgG7FjaKqOqqq/rKq/qi/Prmqbquq3VV1XVU9oo8/sr/e3ZeftNL3BgAAAGByJnFE0S8k+ejY69cleX1r7UlJ7k9yYR+/MMn9ffz1fR4AAAAA68SKGkVVtSXJs5L8Tn9dSX4kyQ19ys4kz+3Pt/XX6cvP6vMBAABYB5wxAqz0iKLfTPKyJP/cXx+X5IHW2v7+ek+Szf355iR3J0lf/mCfDwAAwPrgjBE4wm1a7opV9ewk97bW3l9Vs5MKVFXbk2xPkpmZmczNzS1qvZmjk4tP23/4iUuw2PderH379k18m6thCDllnJyh5AQAYHWNnTHymiQvHTtj5Kf6lJ1JXpnkzRmdMfLKPn5Dkt+qqmqttWlmBiZv2Y2iJD+Y5DlVdU6SRyX5xiRvSHJMVW3qRw1tSbK3z9+b5MQke6pqU5LHJfn8/I221nYk2ZEkW7dubbOzs4sKc/nVN+ay21fycR7urvMW996LNTc3l8V+nrU0hJwyTs5QcgIAsOp+M6MzRh7bXy/6jJGqOnDGyOemlhZYFcvurLTWXpHkFUnSjyj631tr51XVW5P8eJJrk5yf5Ma+yq7++s/78nfpNgMAAKy91TpjpG97yWeNOGNkcoaQcwgZk2HknETGyR6CM/LyJNdW1auT/GWSK/r4FUl+r6p2J7kvybmr8N4AAAAs3aqcMZIs76wRZ4xMzhByDiFjMoyck8g4kf/ltdbmksz153cmOWOBOV9I8hOTeD8AAAAmxxkjwAErvesZwLrl9q4AACv28owubL07o2sQjZ8xclwff2mSS9YoHzBhGkXARub2rgAAS9Ram2utPbs/v7O1dkZr7UmttZ9orX2xj3+hv35SX37n2qYGJkWjCNiQxm7v+jv99YHbu97Qp+xM8tz+fFt/nb78rD4fAADgiKJRBGxUv5nR7V3/ub9e9O1dkxy4vSvAqnBqLACwXq3GXc8A1pTbuy7dEG71mQwj5xAyJsPIOYSMK3Dg1Nhv7K8PnBp7bVX954xOiX1zxk6Nrapz+7yfXIvAAMCRQaMI2Ijc3nWJhnCrz2QYOYeQMRlGziFkXI6xU2Nfk9EFYg+cGvtTfcrOJK/MqFG0rT9PRqfG/lZVlTsLAQCrxalnwIbTWntFa21La+2kJOdmdLvW85K8O6PbtyYL3941cXtXYPX9ZpwaCwCsU44oAo4kL09ybVW9Oslf5mtv7/p7/fau92XUXAKYOKfGLt1QTkEcQs4hZEyGkXMIGQGWS6MI2NBaa3NJ5vrzO5OcscCcLyT5iakGA45UTo1doqGcgjiEnEPImAwj5xAyAiyXU88AAKbEqbEAwHqnUQQAsPZentGFrXdndA2i8VNjj+vjL01yyRrlAwCOEE49AwBYA06NBQDWI0cUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0GkUAAAAAJNEoAgAAAKDTKAIAAAAgiUYRAAAAAJ1GEQAAAABJNIoAAAAA6DSKAAAAAEiiUQQAAABAp1EEAAAAQBKNIgAAAAA6jSIAAAAAkmgUAQAAANBpFAEAAACQRKMIAAAAgE6jCAAAAIAkGkUAAAAAdBpFAAAAACTRKAIAAACg0ygCAAAAIIlGEQAAAACdRhEAAAAASTSKAAAAAOg0igAAAABIsoJGUVWdWFXvrqo7quojVfULffzxVXVzVX28/3tsH6+qemNV7a6qD1XV6ZP6EAAAAACs3EqOKNqf5OLW2qlJnprkoqo6NcklSW5prZ2S5Jb+OkmemeSU/tie5M0reG8AAAAmyMEAQLKCRlFr7Z7W2gf6879P8tEkm5NsS7KzT9uZ5Ln9+bYkb2kjtyY5pqpOWO77AwAAMFEOBgCyaRIbqaqTknxvktuSzLTW7umLPp1kpj/fnOTusdX29LF7xsZSVdszKjKZmZnJ3NzcojLMHJ1cfNr+5X2Ag1jsey/Wvn37Jr7N1TCEnDJOzlByAgCwuvr3uHv687+vqvGDAWb7tJ1J5pK8PGMHAyS5taqOqaoTxr4PAgO04kZRVX1Dkj9I8outtf9ZVV9Z1lprVdWWsr3W2o4kO5Jk69atbXZ2dlHrXX71jbns9on0vb7irvMW996LNTc3l8V+nrU0hJwyTs5QcgIAMD2TPBgAGJYVdVaq6uszahJd3Vp7Wx/+zIEucj+17N4+vjfJiWOrb+ljABNVVScmeUtGOzEtyY7W2huq6vFJrktyUpK7kjyvtXZ/jTrcb0hyTpKHklxw4NRaAIAjzaQPBljOWSPOGJmcIeQcQsZkGDknkXHZjaL+xeqKJB9trf3G2KJdSc5P8tr+741j4y+uqmuTnJnkQYckAqvkwPn1H6iqxyZ5f1XdnOSCjM6vf21VXZLR+fUvz9eeX39mRufXn7kmyYENTSMbWO9W42CA5Zw14oyRyRlCziFkTIaRcxIZV3LXsx9M8m+S/EhVfbA/zsmoQfSjVfXxJE/rr5PkpiR3Jtmd5LeT/NwK3hvgoFxsH1jHXCgWWLcWcTBA8vCDAV7Q73721DgYADaEZbdoW2t/mqQOsvisBea3JBct9/2A5KRL3j7xbV519mMmvs31ZNLn1zt0em0NIecQMibDyDmEjEvlQrHAOnfgYIDbq+qDfeyXM/rj//VVdWGSTyZ5Xl92U0ZHPO7O6KjHF041LbAqJnssH8A6Munz6/t6Dp1eQ0PIOYSMyTByDiHjSrhQLLDeOBgASDSKgA3KxfaB9Ww1GtmOeFxbQ8g5hIzJMHIOISPAcmkUARuOi+0D69lqNbId8bi2hpBzCBmTYeQcQkaA5VrJxawB1isX2wfWJReKBQDWO0cUARuO8+uBdcyFYgGAdU2jCABgSjSyAYD1TqMIAAAAYMpOuuTtE9/mVWc/ZsXbcI0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAAA0GkUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0GkUAAAAAJEk2rXUAAGD4Trrk7RPf5lVnP2bi2wQA4NAcUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAAA0GkUAQAAAJBEowgAAACATqMIAAAAgCQaRQAAAAB0U28UVdXZVfWxqtpdVZdM+/0BDkZ9AtYr9QlYr9Qn2Him2iiqqqOSvCnJM5OcmuT5VXXqNDMALER9AtYr9QlYr9Qn2Jg2Tfn9zkiyu7V2Z5JU1bVJtiW5Y8o5AOZTn4D1Sn2CFTjpkrdPfJtXnf2YiW9zoNQn2ICm3SjanOTusdd7kpw5PqGqtifZ3l/uq6qPLXLbxyf53IoTjmd53SS3lmQVMq6SIeSUcUL+1esWnfOJq51ljR22PiXLrlHq0+QMIecQMiYDyKk+fYX6tM5/V7sh5BxCxmQAOdWnr1Cf1vnvajeEnEPImAwg5yTq07QbRYfVWtuRZMdS16uqv2itbV2FSBMzhIzJMHLKODlDybleLKdGDeFnPISMyTByDiFjMoycQ8i4nqhPa2sIOYeQMRlGziFkXE/Up7U1hJxDyJgMI+ckMk77YtZ7k5w49npLHwNYa+oTsF6pT8B6pT7BBjTtRtH7kpxSVSdX1SOSnJtk15QzACxEfQLWK/UJWK/UJ9iApnrqWWttf1W9OMk7khyV5MrW2kcmtPkln662BoaQMRlGThknZyg5V5X6NIiMyTByDiFjMoycQ8i46tSnQWRMhpFzCBmTYeQcQsZVpz4NImMyjJxDyJgMI+eKM1ZrbRJBAAAAABi4aZ96BgAAAMA6pVEEAAAAQJIBNoqq6uyq+lhV7a6qSxZY/siquq4vv62qTlqHGV9aVXdU1Yeq6paqeuJ6yzg2719XVauqNbkF4GJyVtXz+s/zI1X1++stY1V9c1W9u6r+sv83P2cNMl5ZVfdW1YcPsryq6o39M3yoqk6fdsaNQH2aTsaxeerTCjOqT0cO9Wl6OcfmrVmNUp8mllF9mgL1aXo5x+apTyvIeETUp9baYB4ZXSDtb5N8S5JHJPmrJKfOm/NzSf5zf35ukuvWYcZ/leTR/fm/W48Z+7zHJnlPkluTbF2n/71PSfKXSY7tr//FOsy4I8m/689PTXLXGvwsfyjJ6Uk+fJDl5yT54ySV5KlJbpt2xqE/1KfpZezz1KfJZFSfjoCH+jTdnH3emtUo9WmiOdWn9fG7oD5NKGefpz6tPOOGr09DO6LojCS7W2t3tta+lOTaJNvmzdmWZGd/fkOSs6qq1lPG1tq7W2sP9Ze3JtkyxXyLytj9apLXJfnCNMONWUzOn03yptba/UnSWrt3HWZsSb6xP39ckr+bYr5RgNbek+S+Q0zZluQtbeTWJMdU1QnTSbdhqE9TytipT5PJqD4dGdSnyRlCjVKfJkR9mgr1aXLUp+ll3PD1aWiNos1J7h57vaePLTintbY/yYNJjptKunnv3y2UcdyFGXX6pumwGfuhaSe21t4+zWDzLOZn+W1Jvq2q/qyqbq2qs6eWbmQxGV+Z5Kerak+Sm5K8ZDrRlmSpv7c8nPo0GerT5KhPHKA+Tc4QapT6ND3q08qpT5OjPk2G+pRk08TjsGhV9dNJtib54bXOMq6qvi7JbyS5YI2jLMamjA5PnM2oc/+eqjqttfbAWoaa5/lJrmqtXVZVP5Dk96rqKa21f17rYHAw6tNEqE+wCtZrfUoGVaPUJ1gF6tNEqE/rwNCOKNqb5MSx11v62IJzqmpTRoeCfX4q6ea9f7dQxlTV05L8SpLntNa+OKVsBxwu42OTPCXJXFXdldE5jbvW4GJni/lZ7kmyq7X2T621TyT5m4wKy7QsJuOFSa5Pktbanyd5VJLjp5Ju8Rb1e8shqU+ToT5NjvrEAerT5AyhRqlP06M+rZz6NDnq02SoT8ngLma9KcmdSU7OVy8s9Z3z5lyUr73Y2fXrMOP3ZnSBrFPW689x3vy5rM3FYhfzszw7yc7+/PiMDq87bp1l/OMkF/Tn35HROay1Bj/Pk3Lwi509K197sbP3Tjvf0B/q0/QyzpuvPq0so/p0BDzUp+nmnDd/6jVKfZp4VvVp7X8X1KcJ5Zw3X31afsYNX5+m+kEm9MM4J6Ou4t8m+ZU+9qqMOrfJqJv31iS7k7w3ybesw4z/LclnknywP3att4zz5k69iCzhZ1kZHUJ5R5Lbk5y7DjOemuTPepH5YJKnr0HGa5Lck+SfMurSX5jkRUleNPZzfFP/DLev1X/voT/Up+lknDdXfVpZRvXpCHmoT9PLOW/umtQo9WliGdWn9fG7oD5NKOe8uerT8jNu+PpUfSMAAAAAHOGGdo0iAAAAAFaJRhEAAAAASTSKAAAAAOg0igAAAABIolEEAAAAQKdRBAAAAEASjSIAAAAAOo0iAAAAAJJoFAEAAADQaRQBAAAAkESjCAAAAIBOowgAAACAJBpFAAAAAHQaRQAAAAAk0SgCAAAAoNMoAgAAACCJRhEAAAAAnUYRAAAAAEk0igAAAADoNIoAAAAASKJRBAAAAECnUQQAAABAEo0iAAAAADqNIgAAAACSaBQBAAD///buP9qysrwT/PeJpahoBCW5TYBO0SNtho6toWuQLLPSFUm0xIy41iS2NolgWMNMoo5pSRSTntGY9Fra3caondGmAwFtIhITB6ahYxj0jqtnhPY3KMS2QlCqBFH5EUvG2GWe+eO8pdfiFnV/nLr3nns/n7XOunu/+917P+dQ612c79n73QAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERAAAAAIOgCAAAAIAkgiIAAAAABkERAAAAAEkERQAAAAAMgiIAAAAAkgiKAAAAABgERQAAAAAkERQBAAAAMAiKAAAAAEgiKGIRVTVXVR+uqq9X1ZuPwPG7qp68hH7bR99th9j++qr699OuD9jaljpGAQDAZrToF3C2vAuSfDXJ93d3r3cxAAAAwNpwRdEWdKgrdBb44SS3CokAAABgaxEUbRFVdUdVvaaqbk7yjar6iar6f6vq/qr6dFXtHP0uS3JukldX1b6q+umquqyqfmfBsXZW1Z6Djv1rVXVzVT1QVe+tqkcv2P7rVXVXVX2pqn7poLqeV1WfrKq/rqo7q+r1i5T/S2Pfu6rq1x7mPZ6x2HsCto4xzu0dt85+rqrOrKqjqur3xjjypbF81IJ9VjtGAQDApiEo2lpenOR5Sf5ekquT/E6SJyb5tSR/UlU/0N3nJbkiyb/s7sd19/+1xGO/MMmuJCcn+YdJzkuSqto1jv8zSU5J8tMH7feNJC9Jcsyo7Zer6gUH9fmpse+zk7ymqg4+RqrqhCTXLvaellg/MOOq6ilJXp7kv+vuxyd5TpI7kvxmkjOSPD3J05KcnuSfj32mMUYBAMCmISjaWt7W3Xcm+YUk13X3dd39t919fZKPJTlrlcf+Unffm+T/zOQLWTIJkP6wuz/T3d9I8vqFO3X3fHffMuq4Ocl7kvzjg479W939je6+JckfZhJ4HexIvCdgtnw7yVFJTq2qR3b3Hd39l0nOSfKG7r6nu7+S5LeS/OLYZxpjFAAAbBqCoq3lzvH3h5P8/LhF6/6quj/JTyQ5fhXHvnvB8oNJHjeWf2jBeZPkCwt3qqpnVNWHquorVfVAkv85yXGHqPvA/j+0yPmPxHsCZkh3707yq5mEPfdU1ZVV9UOZjBkLx56F48g0xigAANg0BEVby4HJqe9M8u7uPmbB6+jufuMh9vtGkscuWP87yzjnXUlOWrD+dw/a/kdJrklyUnc/Ick7k9RBfQ7e/0uLnGe57wnYhLr7j7r7JzIJjzvJmzIZM354QbeF48g0xigAANg0BEVb079P8t9X1XOq6hFV9egxQfWJh+j/qSRnVdUTq+rvZPKL/VJdleS8qjq1qh6b5HUHbX98knu7+5tVdXqSf7rIMf7XqnpsVf2DJC9N8t4pvCdgk6mqp1TVs8ZE1d9M8v8l+dtMbhf751X1A1V1XJL/LZMxI5nOGAUAAJuGoGgLGvMUnZ3kN5J8JZOrcX49h/738O4kn85kUtg/z+JBzaHO9R+T/F6SDybZPf4u9CtJ3lBVX8/ky9tVixzm/x773pDkX3f3n0/hPQGbz1FJ3pjkq5ncDvuDSV6byST3H0tyc5JbknxitE1rjAIAgE2juvvwvQAAAADY9FxtAQAAAEASQREAAAAAg6AIAAAAgCSCIgAAAAAGQREAAAAASZJt613AwznuuON6+/btS+r7jW98I0cfffSRLWiVZqHGZDbqVOP0LLXOj3/841/t7h9Yg5JmxlLHqFn4tzALNSazUecs1JjMRp3GJwCAtbehg6Lt27fnYx/72JL6zs/PZ+fOnUe2oFWahRqT2ahTjdOz1Dqr6gtHvprZstQxahb+LcxCjcls1DkLNSazUafxCQBg7bn1DAAAAIAkgiIAAAAABkERAAAAAEkERQAAAAAMgiJgplXVpVV1T1V9ZpFtF1ZVV9VxY72q6m1Vtbuqbq6q0xb0PbeqPj9e567lewAAANgoBEXArLssya6DG6vqpCTPTvLFBc3PTXLKeF2Q5B2j7xOTvC7JM5KcnuR1VXXsEa0aAABgAxIUATOtuz+c5N5FNr0lyauT9IK2s5O8qyduTHJMVR2f5DlJru/ue7v7viTXZ5HwCQAAYLMTFAGbTlWdnWRvd3/6oE0nJLlzwfqe0XaodgAAgC1l23oXADBNVfXYJL+RyW1nR+L4F2Ry21rm5uYyPz9/2H327du3pH7raRZqTGajzlmoMZmNOmehRgCAzUZQBGw2/02Sk5N8uqqS5MQkn6iq05PsTXLSgr4njra9SXYe1D6/2MG7++IkFyfJjh07eufOnYt1+x7z8/NZSr/1NAs1JrNR5yzUmMxGnbNQIwDAZrPiW8+q6ilV9akFr7+uql+tqidW1fXjyUHXH5gQ9uGeNgQwLd19S3f/YHdv7+7tmdxGdlp3353kmiQvGePRGUke6O67knwgybOr6tgxZj17tAEAAGwpKw6Kuvtz3f307n56kn+U5MEk709yUZIbuvuUJDeM9eQQTxsCWI2qek+SjyR5SlXtqarzH6b7dUluT7I7yb9L8itJ0t33JvntJB8drzeMNgAAgC1lWreenZnkL7v7C2MS2Z2j/fJMbt94TRY8bSjJjVV1TFUdP37NB5Zg+0XXTv2Yl+06eurHXEvd/eLDbN++YLmTvOwQ/S5NculUixtu2ftAzpvyf7s73vi8qR4PAAAgmV5Q9KIk7xnLcwvCn7uTzI3lQz1V6HuCopVMFJvMxoSXs1BjMht1btUaL3zq/qkeL5mNzxIAAIC1seqgqKoeleT5SV578Lbu7qrq5RxvJRPFJrMx4eUs1JjMRp1btcZpX5WSTK4o2uifJQAAAGtjxXMULfDcJJ/o7i+P9S9X1fFJMv7eM9oP9bQhAAAAADaAaQRFL853bztLJk8VOncsn5vk6gXtiz1tCAAAAIANYFW3nlXV0Ul+Jsn/tKD5jUmuGk8e+kKSF47265KclcnThh5M8tLVnBsAAACA6VpVUNTd30jypIPavpbJU9AO7nvIpw0BAAAAsP6m9dSzdefx0wAAAACrM405igAAAADYBARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERMMOq6tKquqeqPrOg7V9V1V9U1c1V9f6qOmbBttdW1e6q+lxVPWdB+67RtruqLlrjtwEAALBhCIqAWXZZkl0HtV2f5Ee7+x8m+S9JXpskVXVqkhcl+Qdjn/+9qh5RVY9I8vtJnpvk1CQvHn0BAAC2HEERMLO6+8NJ7j2o7c+7e/9YvTHJiWP57CRXdvffdPdfJdmd5PTx2t3dt3f3t5JcOfoCAABsOdvWuwCAI+iXkrx3LJ+QSXB0wJ7RliR3HtT+jEMdsKouSHJBkszNzWV+fv6wRcw9JrnwqfsP2285lnLe5di3b9/Uj3kkzEKds1BjMht1zkKNAACbjaAI2JSq6jeT7E9yxTSP290XJ7k4SXbs2NE7d+487D5vv+LqvPmW6Q63d5xz+PMux/z8fJbyXtbbLNQ5CzUms1HnLNQIALDZrOrWs6o6pqreNyaOva2qfryqnlhV11fV58ffY0ffqqq3jclib66q06bzFgC+V1Wdl+Rnk5zT3T2a9yY5aUG3E0fbodoBAAC2nNXOUfTWJH/W3T+S5GlJbktyUZIbuvuUJDeM9WQyUewp43VBknes8twAD1FVu5K8Osnzu/vBBZuuSfKiqjqqqk7OZCz6z0k+muSUqjq5qh6VyYTX16x13QAAABvBioOiqnpCkp9MckmSdPe3uvv+TCaBvXx0uzzJC8by2Une1RM3Jjmmqo5f6fkBquo9ST6S5ClVtaeqzk/yb5I8Psn1VfWpqnpnknT3Z5NcleTWJH+W5GXd/e0x8fXLk3wgk7D7qtEXAABgy1nNpBknJ/lKkj+sqqcl+XiSVyaZ6+67Rp+7k8yN5RPy0AljT0hy14K2FU0Um5gsdppmoc6tWuO0/40ns/FZHkp3v3iR5ksepv+/SPIvFmm/Lsl1UywNAABgJq0mKNqW5LQkr+jum6rqrfnubWZJku7uqupF9z6ElUwUm5gsdppmoc6tWuN5F1071eMlyWW7jt7wnyUAAABrYzVzFO1Jsqe7bxrr78skOPrygVvKxt97xnYTxgIAAABsYCsOirr77iR3VtVTRtOZmcz9cU2Sc0fbuUmuHsvXJHnJePrZGUkeWHCLGgAAAADrbLX3ar0iyRXjSUG3J3lpJuHTVWNS2S8keeHoe12Ss5LsTvLg6AsAAADABrGqoKi7P5VkxyKbzlykbyd52WrOBwAAAMCRs5o5igAAAADYRARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERAAAAAIOgCAAAAIAkgiJgxlXVpVV1T1V9ZkHbE6vq+qr6/Ph77GivqnpbVe2uqpur6rQF+5w7+n++qs5dj/cCAACw3gRFwKy7LMmug9ouSnJDd5+S5IaxniTPTXLKeF2Q5B3JJFhK8rokz0hyepLXHQiXAAAAthJBETDTuvvDSe49qPnsJJeP5cuTvGBB+7t64sYkx1TV8Umek+T67r63u+9Lcn0eGj4BAABsetvWuwCAI2Cuu+8ay3cnmRvLJyS5c0G/PaPtUO0PUVUXZHI1Uubm5jI/P3/4Yh6TXPjU/cso//CWct7l2Ldv39SPeSTMQp2zUGMyG3XOQo0AAJvNqoKiqrojydeTfDvJ/u7eMW7heG+S7UnuSPLC7r6vqirJW5OcleTBJOd19ydWc36Aw+nurqqe4vEuTnJxkuzYsaN37tx52H3efsXVefMt083l7zjn8Oddjvn5+Szlvay3WahzFmpMZqPOWagRAGCzmcatZz/V3U/v7h1jfVlzgwAcAV8et5Rl/L1ntO9NctKCfieOtkO1AwAAbClHYo6i5c4NAjBt1yQ58OSyc5NcvaD9JePpZ2ckeWDcovaBJM+uqmPHJNbPHm0AAABbymrvhegkfz5u6/i345aM5c4NcteCthXN/5GYA2SaZqHOrVrjtP+NJ7PxWT6cqnpPkp1JjquqPZk8veyNSa6qqvOTfCHJC0f36zK5/XV3JrfAvjRJuvveqvrtJB8d/d7Q3QdPkA0AALDprTYo+onu3ltVP5jk+qr6i4UbVzI3yErm/0jMATJNs1DnVq3xvIuunerxkuSyXUdv+M/y4XT3iw+x6cxF+naSlx3iOJcmuXSKpQEAAMycVd161t17x997krw/yelZ/twgAAAAAGwAKw6Kquroqnr8geVM5vT4TJY/NwgAAAAAG8Bq7tWaS/L+yVPvsy3JH3X3n1XVR7OMuUEAAAAA2BhWHBR19+1JnrZI+9eyzLlBAAAAAFh/q5qjCAAAAIDNQ1AEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERAAAAAIOgCAAAAIAkgiIAAAAABkERAAAAAEkERQAAAAAMgiIAAAAAkgiKAAAAABgERQAAAAAkERQBAAAAMAiKAAAAAEgiKAI2qar6Z1X12ar6TFW9p6oeXVUnV9VNVbW7qt5bVY8afY8a67vH9u3rXD4AAMC6EBQBm05VnZDkf0myo7t/NMkjkrwoyZuSvKW7n5zkviTnj13OT3LfaH/L6AcAALDlCIqAzWpbksdU1bYkj01yV5JnJXnf2H55kheM5bPHesb2M6uq1q5UAACAjUFQBGw63b03yb9O8sVMAqIHknw8yf3dvX9025PkhLF8QpI7x777R/8nrWXNAAAAG8G21R6gqh6R5GNJ9nb3z1bVyUmuzORL1seT/GJ3f6uqjkryriT/KMnXkvyT7r5jtecHOFhVHZvJVUInJ7k/yR8n2TWlY1+Q5IIkmZuby/z8/GH3mXtMcuFT9x+233Is5bzLsW/fvqkf80iYhTpnocZkNuqchRoBADabVQdFSV6Z5LYk3z/WD8wBcmVVvTOTuT/ekQVzgFTVgblC/skUzg9wsJ9O8lfd/ZUkqao/TfLMJMdU1bZx1dCJSfaO/nuTnJRkz7hV7QmZBNoP0d0XJ7k4SXbs2NE7d+48bDFvv+LqvPmWaQy333XHOYc/73LMz89nKe9lvc1CnbNQYzIbdc5CjQAAm82qbj2rqhOTPC/JH4z1ijlAgPX3xSRnVNVjxzhzZpJbk3woyc+NPucmuXosXzPWM7Z/sLt7DesFAADYEFb7E/fvJXl1kseP9SdliXOAVNWBOUC+uvCAK7mtI3FrxzTNQp1btcZp/xtPZuOzXK7uvqmq3pfkE0n2J/lkJlcBXZvkyqr6ndF2ydjlkiTvrqrdSe7N5AlpAAAAW86Kg6Kq+tkk93T3x6tq57QKWsltHYlbO6ZpFurcqjWed9G1Uz1ekly26+gN/1muRHe/LsnrDmq+Pcnpi/T9ZpKfX4u6AAAANrLVJCvPTPL8qjoryaMzmaPorZnCHCAAAAAArL0Vz1HU3a/t7hO7e3smt2l8sLvPiTlAAAAAAGbSqiazPoTXJHnVmOvjSfneOUCeNNpfleSiI3BuAAAAAFZoKpP6dPd8kvmxbA4QAAAAgBl0JK4oAgAAAGAGCYoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERAAAAAIOgCAAAAIAkgiIAAAAABkERAAAAAEkERQAAAAAMgiJgU6qqY6rqfVX1F1V1W1X9eFU9saqur6rPj7/Hjr5VVW+rqt1VdXNVnbbe9QMAAKwHQRGwWb01yZ91948keVqS25JclOSG7j4lyQ1jPUmem+SU8bogyTvWvlwAAID1t+KgqKoeXVX/uao+XVWfrarfGu0nV9VN45f591bVo0b7UWN999i+fUrvAeB7VNUTkvxkkkuSpLu/1d33Jzk7yeWj2+VJXjCWz07yrp64MckxVXX8mhYNAACwAazmiqK/SfKs7n5akqcn2VVVZyR5U5K3dPeTk9yX5PzR//wk9432t4x+AEfCyUm+kuQPq+qTVfUHVXV0krnuvmv0uTvJ3Fg+IcmdC/bfM9oAAAC2lG0r3bG7O8m+sfrI8eokz0ryT0f75Ulen8ltHGeP5SR5X5J/U1U1jgMwTduSnJbkFd19U1W9Nd+9zSzJZAyrqmWPP1V1QSa3p2Vubi7z8/OH3WfuMcmFT92/3FM9rKWcdzn27ds39WMeCbNQ5yzUmMxGnbNQIwDAZrPioChJquoRST6e5MlJfj/JXya5v7sPfCNa+Kv8d36x7+79VfVAkicl+epqagBYxJ4ke7r7prH+vkyCoi9X1fHdfde4teyesX1vkpMW7H/iaHuI7r44ycVJsmPHjt65c+dhi3n7FVfnzbesarh9iDvOOfx5l2N+fj5LeS/rbRbqnIUak9mocxZqBADYbFb1zaW7v53k6VV1TJL3J/mR1Ra0kl/rE7/YT9Ms1LlVa5z2v/FkNj7L5eruu6vqzqp6Snd/LsmZSW4dr3OTvHH8vXrsck2Sl1fVlUmekeSBBbeoAQAAbBlT+Ym7u++vqg8l+fFMJoHdNq4qWvir/IFf7PdU1bYkT0jytUWOtexf6xO/2E/TLNS5VWs876Jrp3q8JLls19Eb/rNcoVckuWJMqH97kpdmMi/bVVV1fpIvJHnh6HtdkrOS7E7y4OgLAACw5aw4WamqH0jyX0dI9JgkP5PJBNUfSvJzSa7MQ3+xPzfJR8b2D5qfCDhSuvtTSXYssunMRfp2kpcd6ZoAAAA2utVcgnN8ksvHPEXfl+Sq7v4PVXVrkiur6neSfDLj8dTj77uraneSe5O8aBXnBgAAAGDKVvPUs5uT/Ngi7bcnOX2R9m8m+fmVng8AAACAI+v71rsAAAAAADYGQREAAAAASQRFAAAAAAyCIgAAAACSCIoAAAAAGARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERAAAAAIOgCNi0quoRVfXJqvoPY/3kqrqpqnZX1Xur6lGj/aixvnts376uhQMAAKyTFQdFVXVSVX2oqm6tqs9W1StH+xOr6vqq+vz4e+xor6p62/gidnNVnTatNwFwCK9MctuC9TcleUt3PznJfUnOH+3nJ7lvtL9l9AMAANhyVnNF0f4kF3b3qUnOSPKyqjo1yUVJbujuU5LcMNaT5LlJThmvC5K8YxXnBnhYVXVikucl+YOxXkmeleR9o8vlSV4wls8e6xnbzxz9AQAAtpRtK92xu+9KctdY/npV3ZbkhEy+cO0c3S5PMp/kNaP9Xd3dSW6sqmOq6vhxHIBp+70kr07y+LH+pCT3d/f+sb4nkzEr4++dSdLd+6vqgdH/qwcftKouyCTsztzcXObn5w9byNxjkgufuv+w/ZZjKeddjn379k39mEfCLNQ5CzUms1HnLNQIALDZrDgoWmjM5/FjSW5KMrcg/Lk7ydxY/s4XseHAlzRBETBVVfWzSe7p7o9X1c5pHru7L05ycZLs2LGjd+48/OHffsXVefMtUxluv+OOcw5/3uWYn5/PUt7LepuFOmehxmQ26pyFGgEANptVf3Opqscl+ZMkv9rdf73wbo3u7qrqZR5v2b/WJ36xn6ZZqHOr1jjtf+PJbHyWK/DMJM+vqrOSPDrJ9yd5a5JjqmrbuKroxCR7R/+9SU5KsqeqtiV5QpKvrX3ZAAAA62tVQVFVPTKTkOiK7v7T0fzlA7eUVdXxSe4Z7Qe+iB2w8Evad6zk1/rEL/bTNAt1btUaz7vo2qkeL0ku23X0hv8sl6u7X5vktUkyrij6te4+p6r+OMnPJbkyyblJrh67XDPWPzK2f3DcJgsAALClrOapZ5XkkiS3dffvLth04AtX8tAvYi8ZTz87I8kD5icC1thrkryqqnZnMgfRJaP9kiRPGu2vyncn4QcAANhSVnMJzjOT/GKSW6rqU6PtN5K8MclVVXV+ki8keeHYdl2Ss5LsTvJgkpeu4twAS9Ld85lMqp/uvj3J6Yv0+WaSn1/TwgAAADag1Tz17D8lOdTjo89cpH8nedlKzwcAAADAkbXiW88AAAAA2FwERQAAAAAkERQBAAAAMAiKAAAAAEgiKAIAAABgEBQBAAAAkERQBAAAAMAgKAIAAAAgiaAIAAAAgEFQBAAAAEASQREAAAAAg6AIAAAAgCSCIgAAAAAGQREAAAAASQRFAAAAAAyCIgAAAACSCIoAAAAAGARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJKsMiiqqkur6p6q+syCtidW1fVV9fnx99jRXlX1tqraXVU3V9Vpqy0eYDFVdVJVfaiqbq2qz1bVK0e78QkAAOBhrPaKosuS7Dqo7aIkN3T3KUluGOtJ8twkp4zXBUnescpzAxzK/iQXdvepSc5I8rKqOjXGJwAAgIe1qqCouz+c5N6Dms9OcvlYvjzJCxa0v6snbkxyTFUdv5rzAyymu+/q7k+M5a8nuS3JCTE+AQAAPKxtR+CYc91911i+O8ncWD4hyZ0L+u0ZbXcF4Aipqu1JfizJTZnC+FRVF2Ry1VHm5uYyPz9/2BrmHpNc+NT9K3sDh7CU8y7Hvn37pn7MI2EW6pyFGpPZqHMWagQA2GyORFD0Hd3dVdXL2WclX8ISX8SmaRbq3Ko1TvvfeDIbn+VKVdXjkvxJkl/t7r+uqu9sW8n4NPa7OMnFSbJjx47euXPnYfd5+xVX5823THe4veOcw593Oebn57OU97LeZqHOWagxmY06Z6FGAIDN5kgERV+uquO7+65x68Y9o31vkpMW9DtxtH2PlXwJS3wRm6ZZqHOr1njeRddO9XhJctmuozf8Z7kSVfXITEKiK7r7T0fzqsYnAACAzW61k1kv5pok547lc5NcvaD9JePpQmckeWDBLSAAU1OTS4cuSXJbd//ugk3GJwAAgIexqktwquo9SXYmOa6q9iR5XZI3Jrmqqs5P8oUkLxzdr0tyVpLdSR5M8tLVnBvgYTwzyS8muaWqPjXafiPGJwAAgIe1qqCou198iE1nLtK3k7xsNecDWIru/k9J6hCbjU8AAACHcCRuPQMAAABgBgmKAAAAAEgiKAIAAABgEBQBAAAAkERQBAAAAMAgKAIAAAAgiaAIAAAAgEFQBAAAAEASQREAAAAAg6AIAAAAgCSCIgAAAAAGQREAAAAASQRFAAAAAAyCIgAAAACSCIoAAAAAGARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJFmHoKiqdlXV56pqd1VdtNbnBzgU4xMAALDVrWlQVFWPSPL7SZ6b5NQkL66qU9eyBoDFGJ8AAACSbWt8vtOT7O7u25Okqq5McnaSW9e4DoCDGZ9gFbZfdO3Uj3nZrqOnfkwAAB7eWt96dkKSOxes7xltAOvN+AQAAGx5a31F0WFV1QVJLhir+6rqc0vc9bgkX51qLW+a5tGSHIEaj5BZqFONU/JTb1pynT98pGuZBSsco4xP0zMLdc5CjckM1Gl8AgBYe2sdFO1NctKC9RNH23d098VJLl7ugavqY929Y3XlHVmzUGMyG3WqcXpmpc41cNjxKVnZGDULn/Es1JjMRp2zUGMyG3XOQo0AAJvNWt969tEkp1TVyVX1qCQvSnLNGtcAsBjjEwAAsOWt6RVF3b2/ql6e5ANJHpHk0u7+7FrWALAY4xMAAMA6zFHU3dclue4IHHrZt6utg1moMZmNOtU4PbNS5xFnfJoJs1DnLNSYzEads1AjAMCmUt293jUAAAAAsAGs9RxFAAAAAGxQMxcUVdWuqvpcVe2uqosW2X5UVb13bL+pqrZvwBpfVVW3VtXNVXVDVa35Y30PV+OCfv9DVXVVrctTZ5ZSZ1W9cHyen62qP9poNVbV362qD1XVJ8d/87PWocZLq+qeqvrMIbZXVb1tvIebq+q0ta5xMzA+rU2NC/oZn1ZZo/EJAICH6O6ZeWUywexfJvl7SR6V5NNJTj2oz68keedYflGS927AGn8qyWPH8i9vxBpHv8cn+XCSG5Ps2KD/vU9J8skkx471H9yANV6c5JfH8qlJ7liHz/Ink5yW5DOH2H5Wkv+YpJKckeSmta5x1l/Gp7WrcfQzPk2nRuOTl5eXl5eXl5fX97xm7Yqi05Ps7u7bu/tbSa5McvZBfc5OcvlYfl+SM6uqNlKN3f2h7n5wrN6Y5MQ1rG9JNQ6/neRNSb65lsUtsJQ6/8ckv9/d9yVJd9+zAWvsJN8/lp+Q5EtrWN+kgO4PJ7n3YbqcneRdPXFjkmOq6vi1qW7TMD6tUY2D8Wk6NRqfAAD4HrMWFJ2Q5M4F63tG26J9unt/kgeSPGlNqjvo/MNiNS50fia/lK6lw9Y4Lu0/qbuvXcvCDrKUz/LvJ/n7VfX/VNWNVbVrzaqbWEqNr0/yC1W1J5Mnar1ibUpbluX+u+WhjE/TYXyaHuMTAADLtm29C9jKquoXkuxI8o/Xu5aFqur7kvxukvPWuZSl2JbJ7R07M7ny4cNV9dTuvn89izrIi5Nc1t1vrqofT/LuqvrR7v7b9S4MDsX4NBXGJwAAZs6sXVG0N8lJC9ZPHG2L9qmqbZlcSv+1NanuoPMPi9WYqvrpJL+Z5Pnd/TdrVNsBh6vx8Ul+NMl8Vd2RyZwQ16zDhLFL+Sz3JLmmu/9rd/9Vkv+SyReztbKUGs9PclWSdPdHkjw6yXFrUt3SLenfLQ/L+DQdxqfpMT4BALBssxYUfTTJKVV1clU9KpPJYK85qM81Sc4dyz+X5IPd3Rupxqr6sST/NpMvYWs9Z8Vha+zuB7r7uO7e3t3bM5mn5Pnd/bGNVOfwf2Tya32q6rhMbvW4fYPV+MUkZ44a/9tMvoh9ZQ1rXIprkrxkPF3ojCQPdPdd613UjDE+rUGNxqep12h8AgDge8zUrWfdvb+qXp7kA5k8zeXS7v5sVb0hyce6+5okl2Ry6fzuTCbHfNEGrPFfJXlckj8e89h+sbufv8FqXHdLrPMDSZ5dVbcm+XaSX+/uNbtCY4k1Xpjk31XVP8tk4tjz1jgcSFW9J5MvrMeNuUhel+SR4z28M5O5Sc5KsjvJg0leupb1bQbGpzWtcd0Zn6bH+AQAsLHUGv//IAAAAAAb1KzdegYAAADAESIoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAAZBEQAAAABJkv8foRPBrVYJ0d4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1440 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_t.hist(figsize=(20, 20), layout=(3, 4))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's plot binarized variables:\n",
    "\n",
    "variables = data_t.columns.to_list()\n",
    "\n",
    "plt.figure(figsize=(20, 20), constrained_layout=True)\n",
    "\n",
    "for i in range(10):\n",
    "\n",
    "    # location in figure\n",
    "    ax = plt.subplot(3, 4, i + 1)\n",
    "\n",
    "    # variable to plot\n",
    "    var = variables[i]\n",
    "\n",
    "    # determine proportion of observations per bin\n",
    "    t = data_t[var].value_counts(normalize=True)\n",
    "    t.plot.bar(ax=ax)\n",
    "\n",
    "    plt.xticks(rotation=0)\n",
    "    plt.ylabel(\"Observations per bin\")\n",
    "\n",
    "    # add variable name as title\n",
    "    ax.set_title(var)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsml",
   "language": "python",
   "name": "fsml"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "921.556px",
    "left": "0px",
    "right": "1852px",
    "top": "110.444px",
    "width": "281.333px"
   },
   "toc_section_display": "block",
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
